Genomic instability, one of the hallmarks of cancer, is measured in many forms such as chromosomal instability, microsatellite instability, and instability characterized by increased frequency of base-pair mutations (Bakhoum and Cantley, 2018; Pikor et al., 2013; Negrini et al., 2010). Particularly, chromosomal instability (CIN) is associated with cancer progression, tumor immunity, and inflammation (Pikor et al., 2013; Bach et al., 2019). Recently, CIN has been shown to contribute to other diseases than cancer, including neurodegenerative diseases (Hou et al., 2017; Yurov et al., 2019).
Total Aberration Index (TAI) was proposed by (Baumbusch et al., 2013) to measure the genomic aberrations in serous ovarian cancers. TAI calculates absolute area under the curve for a copy number segment profile generated by piecewise constant fitting (PCF) algorithm. Biologically, TAI can be interpreted as absolute deviation from the normal copy number state averaged over all genomic locations. TAI provides a numerical measure in terms of both prevalence as well as the genomic size of copy number variations in tumors. One of the limitations of TAI is that since it was designed for studying advance stage ovarian tumors and short aberrations found in the early tumors have low impact on TAI. Therefore, TAI should be used to study global scale genomic disorganization that most likely occur in late stage tumors.
tai implemented in CINmetrics takes into account only those sample values that are in aberrant copy number state, i.e. has a mean segment values of less than or equal to −0.2 and greater than or equal to +0.2.
Copy Number Abnormality (CNA) was developed by (Davison et al., 2014) for studying aneuploidy in superficial gastroesophageal adenocarcinoma. An individual CNA is defined as the segment with copy number outside the predefined range of 1.7 to 2.3 with the score of 2 indicating no loss or gain (assuming that the tumor is diploid) as determined by Partek segmentation algorithm. Total CNA for the sample can thus be defined as total number of individual CNAs. CNA can be thought of as a measure of segmental aneuploidy. cna implemented in CINmetrics is similar except we define individual CNA as the segment with copy number less than equal to −0.2 and greater than equal to +0.2 with segment mean of 0 indicating no loss or gain. We chose ±0.2 as a conservative cutoff for TCGA data as described in (Laddha et al., 2014). The users can modify the cutoff by modifying segmentMean parameter.
Counting altered base segments and fraction of the genome altered are modified implementation of the Genome Instability Index (GII) as described in (Chin et al., 2007). The GII was computed in two different ways, both based on calculating common regions of alteration (CRA) and both approaches showed high concordance.
fga is based on identifying common regions of alterations as fraction of the genome altered. Therefore, the fga values are normalized by dividing it by the length of the genome covered. countingBaseSegments on the other hand calculates the common regions of alteration.
All the metrics were computed for TCGASARC, TCGA-OV, TCGA-CRC and log10 scaled in order to compare all the meassurements between them.
tai does not capture this global pattern of difference between normal and tumour samples. tai is best suited for late stage cancers, thus should be used as a measure for studying overall genomic disorganization in individual patients with advanced tumours and not as a measure of genomic instability comparison between normal and tumour samples.
tSNE plot showing the clustering of normal and tumor tissue including HRD34 and the CINmetrics signatures.
There is a correlation between HRD34 and the CINmetric signatures except for tai, which is stated by the cinmetrics publication that is a marker of normal or tumors in an earlier stage. In some types of cancer there seems to be a correlation between low HRD and lower breakpoints and cna, however the small data set limits this conclusions and more statistics are needed.
To mathematically and quantitatively describe these alternations we first locate their genomic positions and measure their ranges. Such algorithms are referred to as segmentation algorithms.
I run CINDex in the masked copy number segments from TCGA-SARC downloaded from GDC data commons. Masked copy number segments repport the segment mean which is the log2(copy-number/ 2). However, CINdex requires the CNV values. Therefore, in order to obtain the copy number value:
$$ CNV = 2*2^{mean value}
$$ Settings: CIN for a treshold gain of 2.25, threshold loss of 1.75, unnormalized (indicated by V.def=3), showing overall (gains and losses) CIN (indicated by V.mode=“sum’).
Summary t test for Primary tumor vs Normal tissue CIN per chromosome and sarcoma type:
chr1 Myxofibrosarcoma 1.0051178172904045e-05
chr1 Dedifferentiated liposarcoma 2.3259123305144112e-05
chr1 Leiomyosarcoma (LMS) 0.07726559073095456
chr1 Undifferentiated Pleomorphic Sarcoma (UPS) 8.30682313755901e-05
chr1 Leiomyosarcoma Uterus (LMS) 2.9454347187604525e-08
chr1 Desmoid Tumor 0.05915240534187976
chr2 Myxofibrosarcoma 1.1235849993147825e-06
chr2 Dedifferentiated liposarcoma 0.0004337027393250114
chr2 Leiomyosarcoma (LMS) 0.018345768886121636
chr2 Undifferentiated Pleomorphic Sarcoma (UPS) 0.00012876188082388263
chr2 Leiomyosarcoma Uterus (LMS) 2.994250397435886e-07
chr3 Myxofibrosarcoma 0.003021518906776795
chr3 Dedifferentiated liposarcoma 0.002529565715343376
chr3 Leiomyosarcoma (LMS) 0.048443430264670115
chr3 Undifferentiated Pleomorphic Sarcoma (UPS) 2.4888931880101017e-07
chr3 Leiomyosarcoma Uterus (LMS) 0.0007832445935382686
chr4 Myxofibrosarcoma 0.005768833126575008
chr4 Dedifferentiated liposarcoma 0.012966546272164587
chr4 Leiomyosarcoma (LMS) 0.0008891123729326209
chr4 Undifferentiated Pleomorphic Sarcoma (UPS) 0.0011248851106732097
chr4 Leiomyosarcoma Uterus (LMS) 0.0010550632066550466
chr5 Myxofibrosarcoma 0.002382613677982469
chr5 Dedifferentiated liposarcoma 0.00012092526692431861
chr5 Leiomyosarcoma (LMS) 0.020178443700564243
chr5 Undifferentiated Pleomorphic Sarcoma (UPS) 1.1719489355897795e-05
chr5 Leiomyosarcoma Uterus (LMS) 0.002468702402472995
chr6 Myxofibrosarcoma 0.0015183855856360307
chr6 Dedifferentiated liposarcoma 0.00013367952442730791
chr6 Leiomyosarcoma (LMS) 0.08235384864557929
chr6 Undifferentiated Pleomorphic Sarcoma (UPS) 0.027859816057430965
chr6 Leiomyosarcoma Uterus (LMS) 0.0006210236512757667
chr7 Myxofibrosarcoma 0.007201984054418555
chr7 Dedifferentiated liposarcoma 0.017919024287373676
chr7 Undifferentiated Pleomorphic Sarcoma (UPS) 0.0010141101951651557
chr7 Leiomyosarcoma Uterus (LMS) 0.00012098894031246307
chr7 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.03454305221634289
chr8 Myxofibrosarcoma 0.0007043080357777049
chr8 Dedifferentiated liposarcoma 0.00025266111425827943
chr8 Leiomyosarcoma (LMS) 0.01745740337443614
chr8 Undifferentiated Pleomorphic Sarcoma (UPS) 2.9483136344668342e-05
chr8 Leiomyosarcoma Uterus (LMS) 0.04178157427785321
chr9 Myxofibrosarcoma 0.005236741034189228
chr9 Dedifferentiated liposarcoma 0.0012711729733166728
chr9 Leiomyosarcoma (LMS) 0.015614600591851319
chr9 Undifferentiated Pleomorphic Sarcoma (UPS) 3.895613033074063e-05
chr9 Leiomyosarcoma Uterus (LMS) 0.043728427307502905
chr9 Synovial Sarcoma 0.06651531183539046
chr10 Myxofibrosarcoma 6.449753729392839e-05
chr10 Dedifferentiated liposarcoma 0.03125212093430745
chr10 Leiomyosarcoma (LMS) 0.005665091238527053
chr10 Undifferentiated Pleomorphic Sarcoma (UPS) 5.781787647203919e-06
chr10 Leiomyosarcoma Uterus (LMS) 0.0005450671336302362
chr11 Myxofibrosarcoma 6.7188181034577595e-06
chr11 Dedifferentiated liposarcoma 0.002416002621385722
chr11 Leiomyosarcoma (LMS) 0.09729621161145098
chr11 Undifferentiated Pleomorphic Sarcoma (UPS) 0.0003494004093407973
chr11 Leiomyosarcoma Uterus (LMS) 0.0010770184045157882
chr11 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.06643067518115434
chr11 Desmoid Tumor 0.06810324355436842
chr12 Myxofibrosarcoma 0.014366284631583348
chr12 Dedifferentiated liposarcoma 3.2415905252597296e-14
chr12 Undifferentiated Pleomorphic Sarcoma (UPS) 0.02507697483990025
chr12 Leiomyosarcoma Uterus (LMS) 0.008665117072330008
chr12 Desmoid Tumor 0.008111260168514758
chr13 Myxofibrosarcoma 0.003586918480256585
chr13 Dedifferentiated liposarcoma 0.006419133870745385
chr13 Leiomyosarcoma (LMS) 6.957046453632074e-07
chr13 Undifferentiated Pleomorphic Sarcoma (UPS) 1.5539601750417358e-06
chr13 Leiomyosarcoma Uterus (LMS) 5.7957081460068055e-05
chr14 Myxofibrosarcoma 0.009761248358558482
chr14 Dedifferentiated liposarcoma 0.026970286880360603
chr14 Leiomyosarcoma (LMS) 0.012799892758824821
chr14 Undifferentiated Pleomorphic Sarcoma (UPS) 0.0006192019746325063
chr14 Leiomyosarcoma Uterus (LMS) 9.976968039632079e-05
chr14 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.08401175797305843
chr15 Myxofibrosarcoma 0.01622931145767811
chr15 Dedifferentiated liposarcoma 0.0004216506390224982
chr15 Undifferentiated Pleomorphic Sarcoma (UPS) 0.037000919808370246
chr15 Leiomyosarcoma Uterus (LMS) 0.0004612502665870319
chr15 Synovial Sarcoma 0.07957780650461811
chr16 Myxofibrosarcoma 1.0744045001346349e-06
chr16 Dedifferentiated liposarcoma 0.014093798075528706
chr16 Undifferentiated Pleomorphic Sarcoma (UPS) 1.2384297968903365e-07
chr16 Leiomyosarcoma Uterus (LMS) 0.0003586027150035313
chr17 Myxofibrosarcoma 0.00016706143146382046
chr17 Dedifferentiated liposarcoma 0.014635244805819608
chr17 Leiomyosarcoma (LMS) 5.513126538142558e-05
chr17 Undifferentiated Pleomorphic Sarcoma (UPS) 4.314551172029698e-05
chr17 Leiomyosarcoma Uterus (LMS) 5.806981190910449e-07
chr17 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.0769663868720656
chr18 Myxofibrosarcoma 0.00018699341569055174
chr18 Dedifferentiated liposarcoma 0.004122484262375902
chr18 Leiomyosarcoma (LMS) 0.06426213145455423
chr18 Undifferentiated Pleomorphic Sarcoma (UPS) 0.0006745456508051654
chr18 Leiomyosarcoma Uterus (LMS) 0.03540440974149572
chr19 Myxofibrosarcoma 0.0013362641469685022
chr19 Dedifferentiated liposarcoma 0.00022413612365476934
chr19 Leiomyosarcoma (LMS) 0.0065150696672411626
chr19 Undifferentiated Pleomorphic Sarcoma (UPS) 7.720739545963455e-06
chr19 Leiomyosarcoma Uterus (LMS) 0.006527639097038919
chr19 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.02649842174311059
chr20 Myxofibrosarcoma 9.217286286265104e-06
chr20 Dedifferentiated liposarcoma 0.003182307223562092
chr20 Leiomyosarcoma (LMS) 0.0768587013758429
chr20 Undifferentiated Pleomorphic Sarcoma (UPS) 1.6449280686267801e-06
chr20 Leiomyosarcoma Uterus (LMS) 0.000792150198541933
chr21 Myxofibrosarcoma 0.008470852609419549
chr21 Dedifferentiated liposarcoma 0.06558708183585976
chr21 Leiomyosarcoma (LMS) 0.09751000799818746
chr21 Undifferentiated Pleomorphic Sarcoma (UPS) 0.0180264344716439
chr21 Leiomyosarcoma Uterus (LMS) 0.021798537879322583
chr22 Myxofibrosarcoma 0.0004597661392020043
chr22 Dedifferentiated liposarcoma 0.004719303723295408
chr22 Leiomyosarcoma (LMS) 0.07807566846674234
chr22 Undifferentiated Pleomorphic Sarcoma (UPS) 5.254216503150608e-07
chr22 Leiomyosarcoma Uterus (LMS) 0.04898309593933952
chr22 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.06305385142543547
In general in MFS we can see all the chromosomes with a higher CIN in the Primary tumor compared to Normal except in chromosme 15 and 12.
In ddLPS, chr 21,17,16,14, 10,7, and 4 do not show any difference between primary tumor and normal and chr 1,2,3,5,6,8,9,11,12,13,15,18,19,20 and 22 show a significant difference.
In LMS, chr 19,17,15,13, 12,10,7, and 4 show significant difference between primary tumor and normal, the rest not.
In UPS, chr 6,12,15 and 21 do not show significant difference between primary tumor and normal , the rest do.
In uLMS, chr 22, 21, 18, 9 and 8 do not show significant difference between primary tumor and normal , the rest do.
In MPNST there is no significance found due to the lack of cases.
chr1 Leiomyosarcoma (LMS) 0.0065428376313682425
chr2 Myxofibrosarcoma 0.01083020827333234
chr2 Leiomyosarcoma (LMS) 0.0049314298961821625
chr2 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.002054414893073656
chr3 Leiomyosarcoma (LMS) 0.0026379653450835272
chr3 Undifferentiated Pleomorphic Sarcoma (UPS) 0.029284301193716326
chr3 Leiomyosarcoma Uterus (LMS) 0.015558862651309383
chr4 Leiomyosarcoma (LMS) 0.005923236803770181
chr4 Leiomyosarcoma Uterus (LMS) 0.0038052383915415126
chr5 Leiomyosarcoma (LMS) 0.0049756846202527235
chr5 Undifferentiated Pleomorphic Sarcoma (UPS) 0.036197843924326144
chr5 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.0038181446668229457
chr8 Leiomyosarcoma (LMS) 0.00014155034152748492
chr8 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.014965790107153838
chr9 Leiomyosarcoma (LMS) 0.000900209759460778
chr10 Leiomyosarcoma (LMS) 0.006192211687699704
chr10 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.028731485887760224
chr11 Myxofibrosarcoma 0.033469628089202716
chr11 Leiomyosarcoma (LMS) 0.00025637022114651816
chr11 Leiomyosarcoma Uterus (LMS) 0.008022853142300416
chr11 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.0069482004422070105
chr12 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.027766671064439048
chr13 Dedifferentiated liposarcoma 0.006759242583420783
chr13 Leiomyosarcoma (LMS) 0.00497129514585799
chr13 Undifferentiated Pleomorphic Sarcoma (UPS) 0.049709329524452096
chr14 Leiomyosarcoma (LMS) 2.232655775454952e-05
chr14 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.00603510456533332
chr15 Leiomyosarcoma (LMS) 0.0054219910857945565
chr16 Myxofibrosarcoma 0.0339537664134872
chr17 Leiomyosarcoma (LMS) 0.0036077874699638707
chr18 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.028923506533018575
chr19 Leiomyosarcoma (LMS) 0.018349316703571573
chr19 Undifferentiated Pleomorphic Sarcoma (UPS) 0.04559800338381871
chr19 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.045587208647691294
chr20 Myxofibrosarcoma 0.027514053516250723
chr20 Undifferentiated Pleomorphic Sarcoma (UPS) 0.038665137516787594
chr20 Malignant Peripheral Nerve Sheath Tumors (MPNST) 0.04584624868287656
chr21 Leiomyosarcoma (LMS) 0.00023802599648183194
chr22 Undifferentiated Pleomorphic Sarcoma (UPS) 0.040995095766073665
There are no differences in ddLPs, DT(no HRDhigh group), SS (no HRDhigh group).
There is a High correlation between CINdex and the cna and break points, but there is also certain correlation with fga and base_segments. #### All meassurements
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